This proposal research and develop of a comprehensive new methodology and tool set for medical knowledge management, dissemination, and individualization. The research and development activities include (1) development of an ontology and semantics engine for medical knowledge and patient information from diverse and heterogeneous sources in order to determine best practices and consensus standards of care on a continuous basis, (2) development of decision support and knowledge dissemination tools in order to generate timely, relevant, and individualized care plans and patient education, and (3) development of a continuous feedback methodology and system whereby data gathered from the citizen enables care providers to automatically individualize care plans and patient communications and medical researchers to continuously test and validate rules and associations that drive that individualization.
Additionally, tools will be developed to enable researchers to identify patient characteristics that correlate to disease progression and outcomes and study of disease based on far more detailed patient data, collected at far higher frequency, and on a larger scale than was previously possible. The vast new amounts and sources of data, particularly high frequency data from ubiquitous monitoring outside of the traditional encounter necessitates the development of a new generation of knowledge management tools that automate and integrate the collection, processing and dissemination of medical knowledge to a greater degree than has previously existed.
As these e-health care management tools are disseminated and introduced into clinical practice and medical research, it will become possible for care providers, patients, and researchers to better understand, predict, prevent, and manage disease. The overall goal is to apply and generate medical knowledge in a continuous dynamic feedback process that leads to the lowest achievable risk and cost to society and the highest quality of care and quality of life for citizens.